Semi-field evaluation of freestanding transfluthrin passive emanators and the BG sentinel trap as a "push-pull control strategy" against Aedes aegypti mosquitoes

Spatial repellents that drive mosquitoes away from treated areas, and odour-baited traps, that attract and kill mosquitoes, can be combined and work synergistically in a push-pull system. Push-pull systems have been shown to reduce house entry and outdoor biting rates of malaria vectors and so have the potential to control other outdoor biting mosquitoes such as Aedes aegypti that transmit arboviral diseases. In this study, semi-field experiments were conducted to evaluate whether a push-pull system could be used to reduce bites from Aedes mosquitoes.; The push and pull under investigation consisted of two freestanding transfluthrin passive emanators (FTPE) and a BG sentinel trap (BGS) respectively. The FTPE contained hessian strips treated with 5.25 g of transfluthrin active ingredient. The efficacies of FTPE and BGS alone and in combination were evaluated by human landing catch in a large semi-field system in Tanzania. We also investigated the protection of FTPE over six months. The data were analyzed using generalized linear mixed models with binomial distribution.; Two FTPE had a protective efficacy (PE) of 61.2% (95% confidence interval (CI): 52.2-69.9%) against the human landing of Ae. aegypti. The BGS did not significantly reduce mosquito landings; the PE was 2.1% (95% CI: -2.9-7.2%). The push-pull provided a PE of 64.5% (95% CI: 59.1-69.9%). However, there was no significant difference in the PE between the push-pull and the two FTPE against Ae. aegypti (P = 0.30). The FTPE offered significant protection against Ae. aegypti at month three, with a PE of 46.4% (95% CI: 41.1-51.8%), but not at six months with a PE of 2.2% (95% CI: -9.0-14.0%).; The PE of the FTPE and the full push-pull are similar, indicative that bite prevention is primarily due to the activity of the FTPE. While these results are encouraging for the FTPE, further work is needed for a push-pull system to be recommended for Ae. aegypti control. The three-month protection against Ae. aegypti bites suggests that FTPE would be a useful additional control tool during dengue outbreaks, that does not require regular user compliance

Detection of malaria parasites in dried human blood spots using mid-infrared spectroscopy and logistic regression analysis

Background: Epidemiological surveys of malaria currently rely on microscopy, polymerase chain reaction assays (PCR) or rapid diagnostic test kits for Plasmodium infections (RDTs). This study investigated whether mid-infrared (MIR) spectroscopy coupled with supervised machine learning could constitute an alternative method for rapid malaria screening, directly from dried human blood spots. Methods: Filter papers containing dried blood spots (DBS) were obtained from a cross-sectional malaria survey in 12 wards in southeastern Tanzania in 2018/19. The DBS were scanned using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) spectrometer to obtain high-resolution MIR spectra in the range 4000 cm−1 to 500 cm−1. The spectra were cleaned to compensate for atmospheric water vapour and CO2 interference bands and used to train different classification algorithms to distinguish between malaria-positive and malaria-negative DBS papers based on PCR test results as reference. The analysis considered 296 individuals, including 123 PCR-confirmed malaria positives and 173 negatives. Model training was done using 80% of the dataset, after which the best-fitting model was optimized by bootstrapping of 80/20 train/test-stratified splits. The trained models were evaluated by predicting Plasmodium falciparum positivity in the 20% validation set of DBS. Results: Logistic regression was the best-performing model. Considering PCR as reference, the models attained overall accuracies of 92% for predicting P. falciparum infections (specificity = 91.7%; sensitivity = 92.8%) and 85% for predicting mixed infections of P. falciparum and Plasmodium ovale (specificity = 85%, sensitivity = 85%) in the field-collected specimen. Conclusion: These results demonstrate that mid-infrared spectroscopy coupled with supervised machine learning (MIR-ML) could be used to screen for malaria parasites in human DBS. The approach could have potential for rapid and high-throughput screening of Plasmodium in both non-clinical settings (e.g., field surveys) and clinical settings (diagnosis to aid case management). However, before the approach can be used, we need additional field validation in other study sites with different parasite populations, and in-depth evaluation of the biological basis of the MIR signals. Improving the classification algorithms, and model training on larger datasets could also improve specificity and sensitivity. The MIR-ML spectroscopy system is physically robust, low-cost, and requires minimum maintenance

Global Evolutionary History and Dynamics of Dengue Viruses Inferred from Whole Genome Sequences

Dengue is an arboviral disease caused by dengue virus (DENV), leading to approximately 25,000 deaths/year and with over 40% of the world’s population at risk. Increased international travel and trade, poorly regulated urban expansion, and warming global temperatures have expanded the geographic range and incidence of the virus in recent decades. This study used phylogenetic and selection pressure analyses to investigate trends in DENV evolution, using whole genome coding sequences from publicly available databases alongside newly sequenced isolates collected between 1963–1997 from Southeast Asia and the Pacific. Results revealed very similar phylogenetic relationships when using the envelope gene and the whole genome coding sequences. Although DENV evolution is predominantly driven by negative selection, a number of amino acid sites undergoing positive selection were found across the genome, with the majority located in the envelope and NS5 genes. Some genotypes appear to be diversifying faster than others within each serotype. The results from this research improve our understanding of DENV evolution, with implications for disease control efforts such as Wolbachia-based biocontrol and vaccine design